We also evaluate the image-only transformer-based DiT model [1]}, which itself is a version of the BEiT image transformer [2]}.
Recent work has shown that image transformers often outperform CNN models, and prior work has also found that transformer models outperform other model architectures in terms of out-of-distribution performance (e.g., [3]}, [4]}, [5]}, [6]}; on the contrary, cf. [7]}, [8]} for opposing viewpoints).
Unlike the other models analyzed here, we use the pre-trained DiT model hosted on Hugging Face instead of training the model ourselves.
All models have an input image resolution of 224x224 pixels.
